A Review on Dynamic Prioritization Strategy for Grid Support Using Plug-in Electric Vehicles

Abstract

The increasing adoption of Plug-in Electric Vehicles (PEVs) and the integration of renewable energy sources into power grids necessitate dynamic strategies to optimize grid stability. This review explores cutting-edge dynamic prioritization strategies that manage PEV charging and discharging based on real-time grid conditions. Key findings highlight how advanced control systems, predictive algorithms, and decentralized communication protocols enable PEVs to function as distributed energy resources. These strategies enhance grid flexibility, facilitate demand response, and support peak load shaving while optimizing the integration of renewable energy. The study identifies significant challenges, including scalability, data security, and user participation, and suggests future directions such as leveraging machine learning, blockchain technology, and incentive programs. By addressing these challenges, dynamic prioritization strategies can unlock the full potential of PEVs, fostering a more resilient and sustainable energy system. This review provides critical insights for researchers, policymakers, and industry stakeholders aiming to advance PEV-grid integration.